I have installed the CUDA 9.0.176 version on Ubuntu 14.04.5 LTS, with the nvidia driver below:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.130 Driver Version: 384.130 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 TITAN Xp COLLEC... Off | 00000000:05:00.0 On | N/A |
| 23% 36C P5 18W / 250W | 469MiB / 12187MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce GTX 106... Off | 00000000:06:00.0 Off | N/A |
| 48% 31C P8 11W / 130W | 2MiB / 6072MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1376 G /usr/lib/xorg/Xorg 222MiB |
| 0 2959 G compiz 244MiB |
+-----------------------------------------------------------------------------+
It’s seems my nvidia driver is matched with the CUDA version, but when I was testing the tensorflow, I got an error like this:
InternalError: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
I don’t know why this error happened.